Fix/fallback to 1 when weights doesn't exist & create "tensor" if it …

…doesn't exist (#159)

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "FSRS-Optimizer"
-version = "5.6.4"
+version = "5.6.5"
 readme = "README.md"
 dependencies = [
     "matplotlib>=3.7.0",

src/fsrs_optimizer/fsrs_optimizer.py

@@ -1541,6 +1541,13 @@ def moving_average(data, window_size=365 // 20):
 
     def evaluate(self, save_to_file=True):
         my_collection = Collection(DEFAULT_PARAMETER, self.float_delta_t)
+        if "tensor" not in self.dataset.columns:
+            self.dataset["tensor"] = self.dataset.progress_apply(
+                lambda x: lineToTensor(
+                    list(zip([x["t_history"]], [x["r_history"]]))[0]
+                ),
+                axis=1,
+            )
         stabilities, difficulties = my_collection.batch_predict(self.dataset)
         self.dataset["stability"] = stabilities
         self.dataset["difficulty"] = difficulties
@@ -1551,6 +1558,8 @@ def evaluate(self, save_to_file=True):
             lambda row: -np.log(row["p"]) if row["y"] == 1 else -np.log(1 - row["p"]),
             axis=1,
         )
+        if "weights" not in self.dataset.columns:
+            self.dataset["weights"] = 1
         self.dataset["log_loss"] = (
             self.dataset["log_loss"]
             * self.dataset["weights"]